{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mxnet as mx\n",
    "from mxnet import gluon, nd, autograd\n",
    "from mxnet.gluon import nn, utils\n",
    "import numpy as np\n",
    "import os\n",
    "import tarfile\n",
    "import matplotlib.image as mpimg\n",
    "import matplotlib as mpl\n",
    "from matplotlib import pyplot as plt\n",
    "from time import time\n",
    "%matplotlib inline\n",
    "ctx = mx.gpu()\n",
    "data_dir = '/home/sinyer/python/data/gan'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_data():  \n",
    "    lfw_url = 'http://vis-www.cs.umass.edu/lfw/lfw-deepfunneled.tgz'\n",
    "    data_path = data_dir + '/lfw_dataset'\n",
    "    if not os.path.exists(data_path):\n",
    "        os.makedirs(data_path)\n",
    "        data_file = utils.download(lfw_url)\n",
    "        with tarfile.open(data_file) as tar:\n",
    "            tar.extractall(path=data_path)\n",
    "    img_list = []\n",
    "    for path, _, fnames in os.walk(data_path):\n",
    "        for fname in fnames:\n",
    "            if not fname.endswith('.jpg'):\n",
    "                continue\n",
    "            img = os.path.join(path, fname)\n",
    "            img_arr = mx.image.imread(img)\n",
    "            img_arr = transform(img_arr)\n",
    "            img_list.append(img_arr)\n",
    "    train_data = mx.io.NDArrayIter(data=nd.concatenate(img_list), batch_size=batch_size)\n",
    "    return train_data\n",
    "\n",
    "def transform(data):\n",
    "    data = mx.image.imresize(data, 64, 64)\n",
    "    data = nd.transpose(data, (2,0,1))\n",
    "    data = data.astype(np.float32)/127.5 - 1\n",
    "    if data.shape[0] == 1:\n",
    "        data = nd.tile(data, (3, 1, 1))\n",
    "    return data.reshape((1,) + data.shape)\n",
    "\n",
    "def visualize(img_arr):\n",
    "    plt.imshow(((img_arr.asnumpy().transpose(1, 2, 0) + 1.0) * 127.5).astype(np.uint8))\n",
    "    plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size = 64\n",
    "\n",
    "train_data = load_data()\n",
    "real_label = nd.ones((batch_size,), ctx=ctx)\n",
    "fake_label = nd.zeros((batch_size,), ctx=ctx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "netG = nn.Sequential()\n",
    "with netG.name_scope():\n",
    "    netG.add(nn.Conv2DTranspose(512, 4, 1, 0, use_bias=False))\n",
    "    netG.add(nn.BatchNorm())\n",
    "    netG.add(nn.Activation('relu'))\n",
    "    netG.add(nn.Conv2DTranspose(256, 4, 2, 1, use_bias=False))\n",
    "    netG.add(nn.BatchNorm())\n",
    "    netG.add(nn.Activation('relu'))\n",
    "    netG.add(nn.Conv2DTranspose(128, 4, 2, 1, use_bias=False))\n",
    "    netG.add(nn.BatchNorm())\n",
    "    netG.add(nn.Activation('relu'))\n",
    "    netG.add(nn.Conv2DTranspose(64, 4, 2, 1, use_bias=False))\n",
    "    netG.add(nn.BatchNorm())\n",
    "    netG.add(nn.Activation('relu'))\n",
    "    netG.add(nn.Conv2DTranspose(3, 4, 2, 1, use_bias=False))\n",
    "    netG.add(nn.Activation('tanh'))\n",
    "\n",
    "netD = nn.Sequential()\n",
    "with netD.name_scope():\n",
    "    netD.add(nn.Conv2D(64, 4, 2, 1, use_bias=False))\n",
    "    netD.add(nn.LeakyReLU(0.2))\n",
    "    netD.add(nn.Conv2D(128, 4, 2, 1, use_bias=False))\n",
    "    netD.add(nn.BatchNorm())\n",
    "    netD.add(nn.LeakyReLU(0.2))\n",
    "    netD.add(nn.Conv2D(256, 4, 2, 1, use_bias=False))\n",
    "    netD.add(nn.BatchNorm())\n",
    "    netD.add(nn.LeakyReLU(0.2))\n",
    "    netD.add(nn.Conv2D(512, 4, 2, 1, use_bias=False))\n",
    "    netD.add(nn.BatchNorm())\n",
    "    netD.add(nn.LeakyReLU(0.2))\n",
    "    netD.add(nn.Conv2D(1, 4, 1, 0, use_bias=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "loss = gluon.loss.SigmoidBinaryCrossEntropyLoss()\n",
    "\n",
    "netG.initialize(mx.init.Normal(0.02), ctx=ctx)\n",
    "netD.initialize(mx.init.Normal(0.02), ctx=ctx)\n",
    "\n",
    "trainerG = gluon.Trainer(netG.collect_params(), 'adam', {'learning_rate': 2e-4, 'beta1': 0.5})\n",
    "trainerD = gluon.Trainer(netD.collect_params(), 'adam', {'learning_rate': 2e-4, 'beta1': 0.5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0, dloss 0.7648, gloss 9.9508, T 19.3507\n",
      "1, dloss 0.4750, gloss 7.7703, T 14.1488\n",
      "2, dloss 0.3520, gloss 4.6689, T 14.2108\n",
      "3, dloss 0.3714, gloss 6.2483, T 14.2585\n",
      "4, dloss 1.2852, gloss 6.2802, T 14.3287\n",
      "5, dloss 0.2178, gloss 5.6122, T 14.3842\n",
      "6, dloss 0.1855, gloss 3.6447, T 14.5211\n",
      "7, dloss 0.5246, gloss 6.5644, T 14.6418\n",
      "8, dloss 1.1444, gloss 10.9547, T 14.6763\n",
      "9, dloss 0.1977, gloss 4.4193, T 14.8294\n",
      "10, dloss 0.4562, gloss 4.0105, T 14.6970\n",
      "11, dloss 0.2290, gloss 4.6091, T 14.8421\n",
      "12, dloss 0.3505, gloss 3.4610, T 14.7112\n",
      "13, dloss 0.6388, gloss 7.0825, T 14.7675\n",
      "14, dloss 0.4523, gloss 5.2973, T 14.7501\n",
      "15, dloss 1.6180, gloss 7.7477, T 14.7607\n",
      "16, dloss 0.2720, gloss 3.8735, T 14.8066\n",
      "17, dloss 0.4311, gloss 4.2720, T 14.8807\n",
      "18, dloss 0.3267, gloss 4.0236, T 14.9063\n",
      "19, dloss 1.6406, gloss 6.5126, T 14.8191\n",
      "20, dloss 0.3300, gloss 3.8764, T 14.7128\n",
      "21, dloss 0.3666, gloss 3.4712, T 14.9153\n",
      "22, dloss 0.9287, gloss 6.7739, T 14.8066\n",
      "23, dloss 1.7444, gloss 5.9866, T 14.8057\n",
      "24, dloss 0.3466, gloss 3.6944, T 14.8706\n",
      "25, dloss 0.4696, gloss 2.7151, T 14.8408\n",
      "26, dloss 0.4933, gloss 3.1369, T 14.9120\n",
      "27, dloss 1.9995, gloss 1.2496, T 14.7828\n",
      "28, dloss 0.3622, gloss 3.3335, T 14.8481\n",
      "29, dloss 0.3160, gloss 3.4482, T 14.8754\n",
      "30, dloss 0.6329, gloss 2.3017, T 14.8822\n",
      "31, dloss 0.6502, gloss 4.6505, T 14.7705\n",
      "32, dloss 0.1925, gloss 4.0592, T 14.9271\n",
      "33, dloss 0.2340, gloss 3.6284, T 14.8329\n",
      "34, dloss 0.3788, gloss 3.5395, T 14.8844\n",
      "35, dloss 0.4748, gloss 4.0379, T 14.8687\n",
      "36, dloss 0.3496, gloss 3.0964, T 14.7563\n",
      "37, dloss 0.2990, gloss 3.9310, T 14.8542\n",
      "38, dloss 0.4116, gloss 4.4249, T 14.8566\n",
      "39, dloss 0.3018, gloss 3.5467, T 14.8924\n",
      "40, dloss 0.5898, gloss 5.1492, T 14.8249\n",
      "41, dloss 4.8714, gloss 8.1473, T 14.9219\n",
      "42, dloss 0.4231, gloss 2.6631, T 14.9254\n",
      "43, dloss 0.3314, gloss 4.2649, T 14.7810\n",
      "44, dloss 0.2126, gloss 4.4023, T 14.8154\n",
      "45, dloss 0.2700, gloss 3.9468, T 14.9672\n",
      "46, dloss 0.5975, gloss 4.2416, T 14.8129\n",
      "47, dloss 1.4597, gloss 9.1895, T 14.8050\n",
      "48, dloss 0.2273, gloss 3.2364, T 14.8982\n",
      "49, dloss 1.1634, gloss 9.1793, T 14.9264\n",
      "50, dloss 0.1866, gloss 3.4467, T 14.8740\n",
      "51, dloss 0.2939, gloss 3.0092, T 14.8491\n",
      "52, dloss 0.6113, gloss 2.1748, T 14.7953\n",
      "53, dloss 0.1822, gloss 3.6847, T 14.8534\n",
      "54, dloss 0.1489, gloss 3.5387, T 14.9169\n",
      "55, dloss 0.1312, gloss 4.6452, T 14.9115\n",
      "56, dloss 0.1771, gloss 4.5560, T 14.8212\n",
      "57, dloss 0.1749, gloss 3.5396, T 14.8536\n",
      "58, dloss 0.1097, gloss 4.4430, T 14.9258\n",
      "59, dloss 1.9549, gloss 6.3238, T 14.8249\n",
      "60, dloss 0.1949, gloss 3.2580, T 14.8383\n",
      "61, dloss 0.6191, gloss 4.2372, T 14.8283\n",
      "62, dloss 0.1083, gloss 4.6256, T 14.8088\n",
      "63, dloss 0.0972, gloss 4.4913, T 14.9454\n",
      "64, dloss 0.3526, gloss 4.2092, T 14.7821\n",
      "65, dloss 0.1288, gloss 3.8889, T 14.9618\n",
      "66, dloss 0.0733, gloss 4.0835, T 14.9271\n",
      "67, dloss 0.1264, gloss 3.7987, T 14.7803\n",
      "68, dloss 0.1513, gloss 4.0196, T 14.9803\n",
      "69, dloss 0.1744, gloss 5.7883, T 14.8328\n",
      "70, dloss 0.1139, gloss 5.1807, T 14.7934\n",
      "71, dloss 0.1309, gloss 5.4743, T 14.8314\n",
      "72, dloss 0.3302, gloss 3.4511, T 14.9183\n",
      "73, dloss 0.0855, gloss 4.4207, T 14.9330\n",
      "74, dloss 0.0534, gloss 4.4654, T 14.7727\n",
      "75, dloss 0.0660, gloss 5.0689, T 14.9061\n",
      "76, dloss 0.3225, gloss 3.6483, T 14.9247\n",
      "77, dloss 0.5510, gloss 3.1629, T 14.7362\n",
      "78, dloss 0.1189, gloss 4.7299, T 14.7945\n",
      "79, dloss 0.0466, gloss 4.9056, T 14.9159\n",
      "80, dloss 0.1282, gloss 4.1419, T 14.9429\n",
      "81, dloss 0.0473, gloss 5.0355, T 14.9032\n",
      "82, dloss 0.0503, gloss 5.3048, T 15.0335\n",
      "83, dloss 0.1838, gloss 4.5189, T 15.4113\n",
      "84, dloss 0.0933, gloss 5.0916, T 14.9797\n",
      "85, dloss 0.5780, gloss 6.5248, T 14.7556\n",
      "86, dloss 0.0551, gloss 5.5697, T 14.8185\n",
      "87, dloss 4.9916, gloss 11.3864, T 14.8749\n",
      "88, dloss 0.0787, gloss 4.5247, T 14.9512\n",
      "89, dloss 0.0607, gloss 4.5316, T 14.8294\n",
      "90, dloss 0.0337, gloss 5.5158, T 14.8384\n",
      "91, dloss 0.0358, gloss 5.0939, T 14.9215\n",
      "92, dloss 0.3172, gloss 4.2987, T 14.7948\n",
      "93, dloss 0.1024, gloss 5.5505, T 14.7856\n",
      "94, dloss 0.0649, gloss 5.3258, T 14.8117\n",
      "95, dloss 0.0621, gloss 4.9410, T 14.9809\n",
      "96, dloss 0.0557, gloss 6.0214, T 14.8070\n",
      "97, dloss 0.0449, gloss 5.5361, T 14.8970\n",
      "98, dloss 0.0263, gloss 5.4543, T 14.8725\n",
      "99, dloss 0.6296, gloss 2.6805, T 14.7748\n"
     ]
    }
   ],
   "source": [
    "epochs = 100\n",
    "\n",
    "for epoch in range(epochs):\n",
    "    start = time()\n",
    "    train_data.reset()\n",
    "    for batch in train_data:\n",
    "        data = batch.data[0].as_in_context(ctx)\n",
    "        latent_z = nd.random_normal(0, 1, shape=(batch_size, 100, 1, 1), ctx=ctx)\n",
    "        with autograd.record():\n",
    "            output = netD(data).reshape((-1, 1))\n",
    "            errD_real = loss(output, real_label)\n",
    "            fake = netG(latent_z)\n",
    "            output = netD(fake.detach()).reshape((-1, 1))\n",
    "            errD_fake = loss(output, fake_label)\n",
    "            errD = errD_real + errD_fake\n",
    "            errD.backward()\n",
    "        trainerD.step(batch.data[0].shape[0])\n",
    "        with autograd.record():\n",
    "            fake = netG(latent_z)\n",
    "            output = netD(fake).reshape((-1, 1))\n",
    "            errG = loss(output, real_label)\n",
    "            errG.backward()\n",
    "        trainerG.step(batch.data[0].shape[0])\n",
    "\n",
    "    print('%d, dloss %.4f, gloss %.4f, T %.4f' %(\n",
    "        epoch, nd.mean(errD).asscalar(), nd.mean(errG).asscalar(), time()-start))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_image = 8\n",
    "\n",
    "for i in range(num_image):\n",
    "    latent_z = nd.random_normal(0, 1, shape=(1, 100, 1, 1), ctx=ctx)\n",
    "    img = netG(latent_z)\n",
    "    plt.subplot(2,4,i+1)\n",
    "    visualize(img[0])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
